Introduction

What is this tool?

The MUAC Data Quality and Plausibility Report serves as a crucial tool for assessing the reliability and accuracy of the data collection of MUAC indicators across different assessments. This comprehensive analysis is designed to identify and address potential issues within the data, ensuring that field teams are being informed on potential issues detected in the data collection.

The report provides a detailed examination of the datasets, employing a variety of metrics and methodologies to evaluate data quality and plausibility. This includes checks for completeness, consistency, and accuracy of the data collected. This report aims to uncover any discrepancies, outliers, or anomalies that may suggest data collection, entry errors, or underlying issues that could impact the integrity of the findings.

What is in this tool?

FSL SECTION

This section includes:

  • Overall Plausibility Report / By Enumerator
  • All the flags related to Food Security and Livelihoods (details shown for each flag in the section)
  • Plots showing the distribution of the data.

What to do next?

Please check each flag and the ACTION related to it and act accordingly.

Another output will be associated to this HTML, the Excel file of the flags that were fired and requires follow-up with the field team. Please check the README tab in the excel file. This file will again be generated with the full data during the cleaning of the dataset. So please do use this file during data collection and relate to it in the final one to be filled.

Feedback

Feedback on improvements to this product can be done through reaching out to:

-

-

MUAC

Data Quality MUAC

Plausibility

Overall

Values

flag_name

Excellent

Good

Acceptable

Problematic

Score

plaus_ageratio

p-value > 0.1

p-value > 0.05

p-value > 0.001

p-value < 0.001

3

0

1

3

5

plaus_sexratio

p-value > 0.1

p-value > 0.05

p-value > 0.001

p-value < 0.001

0

0

1

3

5

plaus_dps_muac

< 8

< 13

< 20

>= 20

5

0

1

3

5

plaus_perc_mfaz_children

< 1%

< 3%

< 5%

>= 5%

0

0

5

10

20

plaus_n_children_muac

> 100

> 80

> 50

<= 50

10

0

2

4

10

plaus_sd_muac_mm

< 12

< 14

< 15

>= 15

5

0

5

10

20

plaus_anthro_score

<10

10 < 20

20 < 25

>= 25

23

plaus_anthro_cat

Excellent

Good

Acceptable

Problematic

Acceptable

1

Values

flag_name

Excellent

Good

Acceptable

Problematic

Score

plaus_ageratio

p-value > 0.1

p-value > 0.05

p-value > 0.001

p-value < 0.001

0

0

1

3

5

plaus_sexratio

p-value > 0.1

p-value > 0.05

p-value > 0.001

p-value < 0.001

0

0

1

3

5

plaus_dps_muac

< 8

< 13

< 20

>= 20

5

0

1

3

5

plaus_perc_mfaz_children

< 1%

< 3%

< 5%

>= 5%

0

0

5

10

20

plaus_n_children_muac

> 100

> 80

> 50

<= 50

10

0

2

4

10

plaus_sd_muac_mm

< 12

< 14

< 15

>= 15

10

0

5

10

20

plaus_anthro_score

<10

10 < 20

20 < 25

>= 25

20

plaus_anthro_cat

Excellent

Good

Acceptable

Problematic

Problematic

Overall Flag Table

flag_sd_mfaz

Rational: MUAC-for-age z-scores where the value is greater than +/- 3 from the mean MUAC-for-age z-scores

Action: Data will be automatically cleaned, but please do check with Enumerator.

flag_extreme_muac

Rational: MUAC < 7cm or > 22cm

Action: Data will be automatically cleaned, but please do check with Enumerator.

flag_edema_pitting

Rational: Oedema cases reported “yes”

Action: Manual review and follow-up with team needed to confirm.

Plots

Age in Months Distribution Plot

Age in Months by Team/Enumerator Distribution Plot